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Record W2060451392 · doi:10.2118/167725-ms

Numerous Technological Improvements Slash Drilling Times in the Horn River Basin

2014· article· en· W2060451392 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueSPE/EAGE European Unconventional Resources Conference and Exhibition · 2014
Typearticle
Languageen
FieldEngineering
TopicDrilling and Well Engineering
Canadian institutionsNexen (Canada)
Fundersnot available
KeywordsDrillingDrillPetroleum engineeringCasingWell drillingPetroleumFrench hornAsset (computer security)EngineeringMining engineeringGeologyEnvironmental scienceComputer scienceMechanical engineering

Abstract

fetched live from OpenAlex

Abstract Drilling Performance has improved multifold in the Horn River Basin since the start of activity about four years ago. In its early days a typical well would take about 40 days to drill from spud to cementing the production casing. A range of improvements have happened over the course of last four years which have reduced the drilling time by a factor of 3 despite the wells getting more complex. A number of different technologies have been applied in order to bring these improvements. Some of the examples are pad rig moving system, bigger drill pipe, rotary steerables, managed pressure drilling, high temperature motor elastomers along with time tested project management practices of performance monitoring and improvement by comparison with yardsticks established to challenge the status quo. One such measure of performance is meters per day average achieved from spud to rig release. Some of the recent wells which were drilled to around 5000m accomplished 438 m/day which is an industry record in the Horn River Basin. This was not just a onetime feat. The same performance was repeated on the next two wells. Drilling for Gas in Western Canada is challenged by the price of gas in the current economic environment. Cost cutting by performance improvement provides the means of meeting the challenges posed by this environment. In comparison to the early wells the recent performance offers a cost reduction of 40Million dollars over the course of a 20 well pad, which is significant in determining the net present value of the asset.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.645
Threshold uncertainty score0.602

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.187
Teacher spread0.177 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it